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python - 拟合 Keras 模型时抑制输出

问题描述

我用 Keras 设计了一个神经网络，定义模型后的代码如下：

model.compile(optimizer= 'Adam',loss='mean_squared_error')
##callbacks
cb_checkpoint = ModelCheckpoint("model.h5", monitor='val_loss', save_weights_only=True,save_best_only=True, save_freq=1)
cb_Early_Stop=EarlyStopping( monitor='val_loss',patience=5)
cb_Reduce_LR = ReduceLROnPlateau(monitor='val_loss', factor=0.3, patience=5, verbose=0, mode='auto', min_delta=0.0001, 
                                 cooldown=0, min_lr=0)

callbacks = [cb_checkpoint,cb_Early_Stop,cb_Reduce_LR]
history = model.fit(
          x = {'inputsA': inputsA,  'inputsB': inputsB, 'inputsC': inputsC, 'inputsD': inputsD, 'input_site_id': site_id, 'input_building_id': building_id,  
               'input_meter': meter, 'input_primary_use': primary_use, 
                        'input_week': week, 'input_floor_count': floor_count, 'input_month': month, 'input_hour': hour} , y = {'predictions' : target}, batch_size = 16, epochs = 1000,
    validation_split = 0.1,
            callbacks=callbacks)

当我开始拟合过程时，我会在第一个时期得到这种输出：

Train on 1799857 samples, validate on 199985 samples
Epoch 1/1000
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
     16/1799857 [..............................] - ETA: 60:50:41 - loss: 77.3295WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
    112/1799857 [..............................] - ETA: 8:55:07 - loss: 112.8611WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
    208/1799857 [..............................] - ETA: 4:55:23 - loss: 87.5595 WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
    320/1799857 [..............................] - ETA: 3:17:30 - loss: 78.3782WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
    432/1799857 [..............................] - ETA: 2:29:53 - loss: 70.0334WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Can save best model only with val_loss available, skipping.

我想抑制这个输出，只在每个 epoch 结束时更新 train 和 val loss。

我怎样才能做到这一点？

标签： pythonpython-3.xoutputtensorflow2.0keras-2

解决方案

正如keras 文档中所写，如果输入是生成器或序列，validation_split则将不起作用。

您可以提供validation_data参数。

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